3 papers
cs.LG2026
From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization
Xiaoyu Tao, Shilong Zhang, Mingyue Cheng +5
Time series forecasting plays a vital role in supporting decision-making across a wide range of critical applications, including energy, healthcare, and finance. Despite recent adv…
cs.LG2025
Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization
Qingyang Zhang, Haitao Wu, Changqing Zhang +2
Existing methods to enhance the reasoning capability of large language models predominantly rely on supervised fine-tuning (SFT) followed by reinforcement learning (RL) on reasonin…
stat.ML2024
COME: Test-time adaption by Conservatively Minimizing Entropy
Qingyang Zhang, Yatao Bian, Xinke Kong +2
Machine learning models must continuously self-adjust themselves for novel data distribution in the open world. As the predominant principle, entropy minimization (EM) has been pro…